Category All posts

Geneva, Switzerland – 22 December 2021. Today the Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) standards developing organisation has concluded the year 2022, its first full year of operation approving its fifth standard for publication.

The standards developed and published by MPAI so far are:

1. Context-based Audio Enhancement (MPAI-CAE) – approved today – supports 4 identified use cases: adding a desired emotion to an emotion-less speech segment, preserving old audio tapes, restoring audio segments and improving the audio conference experience.
2. AI Framework (MPAI-AIF) enables creation and automation of mixed Machine Learning, Artificial Intelligence, Data Processing and inference workflows. The Framework can be implemented as software, hardware, or hybrid software and hardware.
3. Compression and Understanding of Industrial Data (MPAI-CUI) gives the financial risk assessment industry new, powerful and extensible means to predict the performance of a company several years into the future.
4. Multimodal Conversation (MPAI-MMC) enables advanced human-machine conversation forms such as: holding an audio-visual conversation with a machine impersonated by a synthetic voice and an animated face; requesting and receiving information via speech about a displayed object; inter­preting speech to one, two or many languages using a synthetic voice that preserves the features of the human speech.
5. Governance of the MPAI Ecosystem (MPAI-GME) lays down the rules governing an ecosystem of implem­enters and users of secure MPAI standard im­plemen­tations guar­an­teed for Conformance and Performance, and acces­sible through the not-for-profit MPAI Store.

The Book “Towards Pervasive and Trustworthy Artificial Intelligence” illustrates the results achieved by MPAI in its 15 months of operation and the plans for the next 12 months.

MPAI is currently working on several other standards, some of which are:

1. Server-based Predictive Multiplayer Gaming (MPAI-SPG) uses AI to train a network that com­pensates data losses and detects false data in online multiplayer gaming.
2. AI-Enhanced Video Coding (MPAI-EVC), a candidate MPAI standard improving existing video coding tools with AI and targeting short-to-medium term applications.
3. End-to-End Video Coding (MPAI-EEV) is a recently launched MPAI exploration promising a fuller exploitation of the AI potential in a longer-term time frame that MPAI-EVC.
4. Connected Autonomous Vehicles (MPAI-CAV) uses AI in key features: Human-CAV Interac­tion, Environment Sensing, Autonomous Motion, CAV to Everything and Motion Actuation.
5. Mixed Reality Collaborative Spaces (MPAI-MCS) creates AI-enabled mixed-reality spaces populated by streamed objects such as avatars, other objects and sensor data, and their descriptors for use in meetings, education, biomedicine, science, gaming and manufacturing.

MPAI develops data coding standards for applications that have AI as the core enabling technology. Any legal entity supporting the MPAI mission may join MPAI if able to contribute to the development of standards for the efficient use of data.

Visit the MPAI web site and contact the MPAI secretariat for specific information.

Fifteen months after coming into life and celebrating the successful development of 5 major AI-based data coding standards, MPAI has published the book “Towards Pervasive and Trustworthy Artificial Intelligence: How standards can put a great technology at the service of humankind”.

For the authors, representatives of the articulated MPAI world, it has been quite an effort but rewarded by the sight of the published book, now available online.

In its 110 B5 pages the book offers

1. A summary of the reasons that have led to the creation of MPAI
2. An analysis of the promises but also the potential dangers of AI
3. An overview of the main Machine Learning and Neural Network technologies
4. An analysis of state of the art of data coding in some of the fields addressed by MPAI:
   1. Speaking humans and machines
   2. Visual humans and machines
   3. Humans conversing with machines
   4. Audio for humans
   5. Video for humans and machines
   6. Data for machines
5. An introduction to the measures Europe, USA and China are taking to regulate AI
6. A description of the why we need, how we implement and what are the benefits of the AI Framework
7. A brief introduction to some of the key applications supported by the first MPAI standards
   1. Conversation with emotion
   2. Conversation about an object
   3. Feature-preserving speech translation
   4. Emotion enhanced speech
   5. Speech restoration system
   6. Audio recording preservation
   7. Enhanced audioconference experience
   8. Company performance prediction
8. An explanation of what is an MPAI standard, a collection of
   1. Technical Specification
   2. Reference Software
   3. Conformance Testing
   4. Performance Assessment
9. A presentation of some of the technologies already standardised by MPAI
   1. Emotion
   2. Intention
   3. Meaning
   4. Speech features
   5. Microphone array geometry
   6. Audio scene geometry
10. Some words about the “fuel” and the “machine” that drives MPAI standardisation
11. The plan adopted by MPAI to govern its sophisticated ecosystem
12. MPAI’s views of the vital role of patents and how it can be preserved
13. An anticipation of the coming MPAI standards
    1. AI-enhanced video coding
    2. End-to-end video coding
    3. Server-based predictive multiplayer gaming
    4. Connected autonomous vehicles
    5. Conversation about a scene
    6. Mixed-reality collaborative spaces
    7. Audio on the go
14. The 7 impacts MPAI standardisation are expected to have on industry, innovation and users.

What should be expected from this book?

• For you, an opportunity to benefit yourself from the hard work of some 20 people distilling the most important information generated in the last 15 months by MPAI and also to share the opportunity with friends.
• For MPAI the opportunity to welcome more of you on board this exciting initiative.
• For me the unique experience of working with outstanding people in the editing of the book.
• For all, best wishes for the coming holydays!

For about a year, MPAI has developed Use Cases and Functional Requirements for the Connected Autonomous Vehicles (MPAI-CAV) project, and the document has reach good maturity. MPAI is now publishing the results achieved so far on this and other web sites, on social networks and newsletters.

Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) is an international, unaffiliated, non-profit organisation with the mission is to develop Artificial Intelligence (AI) enabled data coding specifications, with clear Intellectual Property Rights (IPR) licensing frameworks. The scope of data coding includes any instance in which digital data needs to be converted to a different format to suit a specific application. Notable examples are: compression and feature extraction.

MPAI-CAV is an MPAI project seeking to standardise the components required to implement a Connected Autonomous Vehicle (CAV). MPAI defines a CAV as a mechanical system capable of moving autonomously – save for the exceptional intervention of a human – based on the analysis of the data produced by a range of sensors exploring the environment and the information transmitted by other sources in range, e.g., CAVs and roadside units (RSU).

This is the first of several articles reporting about the progress achieved and the developments planned in the MPAI-CAV project.

The current focus is the development of Use Cases and Functional Requirements (MPAI-CAV UCFR), the first step towards publishing a Call for Technologies. Responses to the Call will then enable MPAI to actually develop the MPAI-CAV standard.

There are 3 ways for you to get involved in the MPAI-CAV project:

1. Monitor the progress of the MPAI-CAV project.
2. Participate in MPAI-CAV activities (confcall meetings) as a non-member.
3. Join MPAI as a member.

MPAI invites professionals and researchers to contribute to further developing the MPAI-CAV UCFR.

MPAI-CAV has identified 5 main subsystems of a Connected Autonomous Vehicle, as depicted in Figure 1.

Figure 1 – The 5 MPAI-CAV subsystems

The functions of the individual subsystems can be described as follows:

1. Human-CAV interaction (HCI) recognises the human CAV rights holder, responds to humans’ commands and queries, provides extended environment representation (Full World Representation) for humans to use, senses human activities during the travel and may activate other Subsystems as required by humans.
2. Environment Sensing Subsystem (ESS) acquires information from the environment via a variety of sensors and produces a representation of the environment (Basic World Representation), its best guess given the available sensory data.
3. Autonomous Motion Subsystem (AMS) computes the Route to destination, uses different sources of information – CAV sensors, other CAVs and transmitting units – to produce a Full World Representation and gives commands that drive the CAV to the intended destination.
4. CAV to Everything Subsystem (V2X) sends/receives information to/from external sources, including other CAVs, other CAV-capable vehicles, Roadside Units (RSU).
5. Motion Actuation Subsystem (MAS) provides non-electromagnetic information anout the environment¸ receives and actuates motion commands in the environment.

The next publications will deal with

1. Why an MPAI-CAV standard?
2. Introduction to MPAI-CAV Subsystems
3. Human-CAV interaction
4. Environment Sensing Subsystem
5. CAV to Everything
6. Autonomous Motion Subsystem
7. Motion Actuation Subsystem

For any communication or intention to join MPAI-CAV activities, or any other MPAI standards development activities, send an email to Secretariat (secretariat@mpai.community).

1. MPAI develops standards and Standards accelerate technology exploitation into products.
2. MPAI standards are Artificial Intelligence-enabled and AI has the highest potential to yield high-performance solutions to data coding.
3. MPEG has shown that standards should be developed by applying a given technology across the board and MPAI is the only standards organisation doing so for AI-based data coding.
4. MPEG has shown that industry is well served by increasing accessibility to standards and MPAI makes available Framework Licences to accelerate access to its standards.
5. MPAI has solid foundations: it has experience and a rigorous standards-development process.
6. MPAI addresses high-profile data coding areas: AI framework, audio enhancement, human-machine conversation, prediction of company performance, video coding, online gaming, autonomous vehicles and more.
7. MPAI is productive: in 15 months it has developed 4 standards (governance, human-machine conversation, company performance prediction and AI Framework), by end of year it will complete another standard (audio enhancement) and has 7 more standards in the pipeline.
8. MPAI standards are viral: products conforming to MPAI standards are already present on the market.
9. MPAI develops methods to assess the level of conformance and reliability of standard implementations, including methods ensuring that implementations are bias-free.
10. MPAI plans on establishing the MPAI Store, a not-for-profit commercial organisation with the task to test implementations for security and conformance, and verify they are bias-free

Join the fun, build the future!

1. MPAI develops standards, unique means to accelerate exploitation of technology in products.
2. MPAI standards are Artificial Intelligence-enabled and AI has the highest potential to yield high-performance solutions to data coding.
3. MPEG has shown that standards should be developed by applying technology across the board and MPAI is the only standards organisation doing so for AI-based data coding.
4. MPEG has shown that industry is well served by increasing accessibility to standards and MPAI makes available Framework Licences to accelerate access to its standards.
5. MPAI has solid foundations: it has experience and a rigorous standards-development process.
6. MPAI addresses high-profile data coding areas: AI framework, audio enhancement, human-machine conversation, prediction of company performance, video coding, online gaming, autonomous vehicles and more.
7. MPAI is productive: in 15 months it has developed 4 standards (governance, human-machine conversation, company performance prediction and AI Framework), by end of year it will complete another standard (audio enhancement) and has 7 more standards in the pipeline.
8. MPAI standards are viral: products conforming to MPAI standards are already present on the market.
9. MPAI develops methods to assess the level of conformance and reliability of standard implementations, including methods ensuring that implementations are bias-free.
10. MPAI plans on establishing the MPAI Store, a not-for-profit commercial organisation with the task to test implementations for security and conformance, and verify they are bias-free.

    Join the fun, build the future!

Geneva, Switzerland – 24 November 2021. After releasing 3 official standards, today the Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) standards developing organisation has published one standard for final publication and one draft standard for Community Comments, the step before official release.

The standard approved for final publication is AI Framework (MPAI-AIF), a standard that enables creation and automation of mixed Machine Learning, Artificial Intelligence, Data Processing and inference workflows. The Framework can be implemented as software, hardware, or hybrid software and hardware, and is the enabler of the MPAI Store, a not-for-profit entity giving access to certified MPAI implementations.

The draft standard released for Community Comments is Context-based Audio Enhancement (MPAI-CAE). The standard supports 4 identified use cases: adding a desired emotion to an emotion-less speech segment, preserving old audio tapes, restoring audio segments and improving the audio conference experience. Comments are requested, by 15 December, prior to final approval at MPAI’s next General Assembly (MPAI-15) on 22 December 2021.

MPAI is currently working on several other standards, some of which are:

1. Server-based Predictive Multiplayer Gaming (MPAI-SPG) uses AI to train a network that com­pensates data losses and detects false data in online multiplayer gaming.
2. AI-Enhanced Video Coding (MPAI-EVC), a candidate MPAI standard improving existing video coding tools with AI and targeting short-to-medium term applications.
3. End-to-End Video Coding (MPAI-EEV) is a recently launched MPAI exploration promising a fuller exploitation of the AI potential in a longer-term time frame that MPAI-EVC.
4. Connected Autonomous Vehicles (MPAI-CAV) uses AI in key features: Human-CAV Interac­tion, Environment Sensing, Autonomous Motion, CAV to Everything and Motion Actuation.
5. Mixed Reality Collaborative Spaces (MPAI-MCS) creates AI-enabled mixed-reality spaces populated by streamed objects such as avatars, other objects and sensor data, and their descriptors for use in meetings, education, biomedicine, science, gaming and manufacturing.

So far MPAI has published 4 standards in final form

1. The AI Framework (MPAI-AIF) standard.
2. The Governance of the MPAI Ecosystem (MPAI-GME) establishing the process and rules that allow users to select and access implementations with the desired interoperability level.
3. The Compression and Understanding of Industrial Data (MPAI-CUI) standard giving the financial risk assessment industry new, powerful and extensible means to predict the performance of a company.
4. The Multimodal Conversation (MPAI-MMC) standard allowing industry to accelerate the availability of products, services and applications such as: multimodal conversation with a machine; requesting and receiving information via speech about a displayed object; translating speech using a synthetic voice that preserves the features of the speaker.

MPAI develops data coding standards for applications that have AI as the core enabling technology. Any legal entity supporting the MPAI mission may join MPAI if able to contribute to the development of standards for the efficient use of data.

Visit the MPAI web site and contact the MPAI secretariat for specific information.

Are there serious reasons to be part of the Moving Picture, Audio and Data Coding by Artificial Intelligence?

The latest is the fact that, starting from the 20^th of November 2021, a legal entity or a representative of an academic department who are able to contribute to the the development of Technical Specifications can join MPAI now and have their membership extended until the end of 2022.

This, however, is more an opportunity to accelerate the decision to joinMPAI, because there are other substantive reasons:

1. Data coding is a very important technology area.
2. Standards accelerate technology exploitation into products.
3. AI is the technology with the highest potential to yield high-performance solutions.
4. MPEG has shown that standards should be developed by applying technology across the board and MPAI is the only standards organisation doing so for AI-based data coding.
5. MPEG has shown that standards should be accessible and MPAI applies the practice of making available Framework Licences to accelerate accessibility to its standards.
6. MPAI has solid foundations, experience and a rigorous standards-development process.
7. MPAI addresses high-profile areas: AI framework, audio enhancement, human-machine conversation, prediction of company performance, video coding, online gaming, autonomous vehicles and more.
8. MPAI is productive: in 15 months it has developed 3 standards (governance, human-machine conversation and company performance prediction), by end of year it will complete 2 standards (AI framework and audio enhancement) and has 7 more standards in the pipeline.
9. MPAI standards are viral: products conforming to MPAI standards are already present on the market.
10. MPAI develops methods to assess the level of conformance and reliability of standard implementations, including methods ensuring that implementations are bias-free.
11. MPAI plans on establishing MPAI Store, a not-for-profit commercial organisation with the task to test implementations for security and conformance, and verify they are bias-free.

Join the fun, build the future!

MPAI – the international AI-based data coding standards developing organisation – has published an epoch-marking AI-based standard called MPAI-CUI (Compression and Understanding of Industrial Data) that allows the assessment of a company from its financial, governance and risk data.

An implementation of the standard is composed of several modules pre-processing the input data. A fourth module – called Prediction – is a neural network that has been trained with a large amount of company data of the same type as those used by the implementation and can provide an accurate estimate of the company default probability and the governance adequacy. The fifth module – called Perturbation – takes as input the estimation of the company default probability and the assessment of vertical risks (i.e., seismic and cyber) and estimates the probability that a business discontinuity will occur in the future.

The MPAI-CUI standard is complemented by a second specification called Conformance Assessment. This allows a user of an implementation of the standard to verify that the implementation is technically correct.

The standard is further complemented by a specification called Performance Assessment. The goal of the specification is to allow a user to detect whether the training of the neural network was biased against some geographic locations (e.g., North-South) and some industry types among the four currently supported: service, public, commerce and manufacturing.

The novelty of MPAI-CUI is in its ability to analyse, through AI, the large amount of data required by regulation and extract the most relevant information. Moreover, compared to state-of-the-art techniques that predict the performance of a company, MPAI-CUI allows extending the time horizon of prediction.

Companies and financial institutions can use MPAI-CUI in a variety of contexts, e.g.:

1. To support the company’s board in deploying efficient strategies. A company can analyse its financial performance, identifying possible clues to the crisis or risk of bankruptcy years in advance. It may help the board of directors and decision-makers to make the proper decisions to avoid these situations, conduct what-if analysis, and devise efficient strategies.
2. To assess the financial health of companies applying for funds/financial help. A financial institution receiving a request for financial help from a troubled company, can access the company’s financial and organisational data and make an AI-based assessment, as well as a prediction of future performance of the company. This helps the financial institution to make the right decision whether funding that company or not, based on a broad vision of its situation.

MPAI organises a public workshop to promote understanding and potential of use of MPAI-CUI in the industry. The event will be held on 25^th of November 2021 at 15:00 UTC with the following agenda:

1. Introduction (5’) – will introduce MPAI, its mission, what has been done in the year after its establisment, plans
2. MPAI-CUI standard (15’) – will describe
   1. The process that led to the standard: study of Use Cases, Functional Requirements, Commercial Requirements, Call for Technologies, Request for Community Comments and Standard.
   2. The MPAI-CUI modules and their function.
   3. Extensions under way.
   4. Some applications of the standard (banking, insurance, public administrations).
3. Demo (15’) – a set of anonymous companies with identified financial, governance and risk features will be passed through an MPAI-CUI implementation.
4. Q&A

Geneva, Switzerland – 27 October 2021. After releasing 3 official standards at its previous monthly General Assembly, today the Moving Pic­ture, Audio and Data Coding by Artificial Intelligence (MPAI) standards developing organisation has published 1 more draft standard for comments, the step before official release.

Comments are requested, by 20 November, prior to final approval at MPAI’s next 24 November General Assem­bly (MPAI-14) on:

AI Framework (MPAI-AIF) enables creation and autom­ation of mixed Machine Learning, Artificial Intelligence, Data Processing and inference workflows, implemented as software, hardware, or hybrid software and hardware. MPAI-AIF is also an enabler of the MPAI Store part of the Governance of the MPAI Ecosystem (MPAI-GME) approved by MPAI-12.

MPAI-12 released the full set of the AI-based Compression and Understanding of Industrial Data (MPAI-CUI) standard – Technical Specification, Reference Software, Conformance Testing and Performance Assessment. As MPAI-12 only released the Multimodal Conversation (MPAI-MMC) Technical Specification, MPAI is currently developing the MPAI-MMC Conformance Testing specification to enable a user to verify the technical correctness of an implementation.

MPAI is currently working on several other standards, e.g.:

1. Context-based Audio Enhancement (MPAI-CAE): adding a desired emotion to an emotion-less speech segment, preserving old audio tapes, restoring audio segments and improving the audio confer­ence experience.
2. Server-based Predictive Multiplayer Gaming (MPAI-SPG) uses AI to train a network that com­pensates data losses and detects false data in online multiplayer gaming.
3. Connected Autonomous Vehicles (MPAI-CAV) uses AI in key features: Human-CAV Interac­tion, Environ­ment Sensing, Autonomous Motion, CAV to Everything and Motion Actuation.
4. Mixed Reality Collaborative Spaces (MPAI-MCS) creates AI-enabled mixed-reality spaces populated by streamed objects such as avatars, other objects and sensor data, and their descriptors for use in meetings, education, biomedicine, science, gaming and manufacturing.
5. AI-Enhanced Video Coding (MPAI-EVC), a candidate MPAI standard improving existing video coding tools with AI and targeting short-to-medium term applications.
6. End-to-End Video Coding (MPAI-EEV) is a recently launched MPAI exploration promising a fuller exploitation of the AI potential in a longer-term time frame that mPAI-EVC.

MPAI develops data coding standards for applications that have AI as the core enabling technology. Any legal entity who supports the MPAI mission may join MPAI if it is able to contribute to the development of standards for the efficient use of data.

Visit the MPAI web site and contact the MPAI secretariat for specific information.

Geneva, Switzerland – 30 September 2021. Today, at its 12^th General Assembly, the Moving Pic­ture, Audio and Data Coding by Artificial Intelligence (MPAI) standards devel­oping organisation has approved 3 standards for publication.

Established exactly one year ago as an international, unaffili­ated, not for profit association, MPAI is proud to announce that the first two AI-powered standards approved today serve two of the many industries targeted by MPAI: financial risk assessment and human-to-machine communication.  MPAI standards generate an ecosystem whose governance constitutes the 3^rd standard approved today.

The AI-based Compression and Understanding of Industrial Data (MPAI-CUI) standard gives the financial risk assessment industry new, powerful and extensible means to predict the performance of a company. The standard includes Reference Software, Conformance Testing (to test that the standard has been correctly implemented) and Performance Assessment (to assess how well an im­plem­entation satis­fies the criteria of Reliability, Robustness, Replicab­ility and Fairness). The Reference Software is released with a modified BSD licence (link). An online demo (link) demonstrates the potential of the MPAI-CUI standard.

A slate of applications are enabled by the approved Multimodal Conversation (MPAI-MMC) standard. Industry can accelerate the availability of products, services and applications such as: holding an audio-visual conversation with a machine impersonated by a synthetic voice and an animated face; requesting and receiving information via speech about a displayed object; inter­preting speech to one, two or many languages using a synthetic voice that preserves the features of the human speech.

AI is a technology with great potential for good but also misleading use. With the document Governance of the MPAI Ecosystem (MPAI-GME) approved today, MPAI has laid down the rules governing an ecosystem of implem­enters and users of secure MPAI standard im­plemen­tations guar­an­teed for Conformance and Performance, and acces­sible through the not-for-profit MPAI Store.

All standards can be downloaded from the MPAI web site.

MPAI has been working on AI-Enhanced Video Coding (MPAI-EVC), a candidate MPAI standard improving existing video coding tools with AI and targeting short-to-medium term applications. MPAI believes that the so-called end-to-end approach lends itself to a fuller exploitation of the AI potential. Therefore, MPAI is launching a new project called AI-based End-to-End Video Coding (MPAI-EEV) targeting long-term applications next to MPAI-EVC.

MPAI has also decided to approve the following two draft standards for community comments:

1. Context-based Audio Enhancement (MPAI-CAE): adding a desired emotion to an emotion-less speech segment, preserving old audio tapes, restoring audio segments, improving the audio confer­ence experience and removing unwanted sounds to a user on the go.
2. AI Framework (MPAI-AIF) enables creation and autom­ation of mixed Machine Learning, Artificial Intelligence, Data Processing and inference workflows, implemented as software, hardware, or hybrid software and hardware.

MPAI is currently also working on several other standards, e.g.:

1. Server-based Predictive Multiplayer Gaming (MPAI-SPG) uses AI to train a network that com­pensates data losses and detects false data in online multiplayer gaming.
2. Connected Autonomous Vehicles (MPAI-CAV) uses AI in key features: Human-CAV Interac­tion, Environ­ment Sensing, Autonomous Motion, CAV to Everything and Motion Actuation.
3. Mixed Reality Collaborative Spaces (MPAI-MCS) creates AI-enabled mixed-reality spaces populated by streamed objects such as avatars, other objects and sensor data, and their descriptors for use in meetings, education, biomedicine, science, gaming and manufacturing.

MPAI develops data coding standards for applications that have AI as the core enabling technology. Any legal entity who supports the MPAI mission may join MPAI if it is able to contribute to the development of standards for the efficient use of data.

Visit the MPAI web site and contact the MPAI secretariat for specific information.